IInternals DecodedOct 23 · 14 min readHallucination Detection: Trust, but VerifyThroughout the AI System Design series we follow Mailmind, a fictional AI email assistant that reads an inbox, triages messages, and drafts replies. It is our running example. Before you read: Why Minternals-decoded.hashnode.dev
EEUNMIN PARKOct 20 · 9 min readMy AI Invented My Past. A 472-Year-Old Archive Knew the Fix.This week, the AI I work with every day told me about my own life. Three times. All three were false. It said I asked Matthias Troyer a question at his QCE26 keynote. I never did. Corrected, it said Ieunminpark.hashnode.dev
GGangsta AISep 16 · 4 min readCatching AI Hallucinations With Multi-Model ConsensusThe scariest AI failure isn't the obvious mistake. It's the confident one — the fabricated citation, the plausible-but-wrong number, the invented API method that compiles in your head but not in realigangstaai.hashnode.dev
IInternals DecodedAug 29 · 11 min readWhy Models Make Things UpLast time, we saw how a model's working memory, its context window, can get overloaded, causing long conversations to drift. This time we tackle the most infamous side effect of that same predictive einternals-decoded.hashnode.dev
RRaul CastellanosAug 22 · 4 min readReduce AI Agents Hallucinations: Deterministic Software Engineering with the QRSPI Agent SkillThe Problem: Why Autonomous AI Agents Still Break Codebases If you have used autonomous AI coding assistants (such as Claude Code, Google Gemini / Antigravity, Cursor, OpenAI Codex, or OpenCode) on noblog.equationlabs.io
HHimaniJul 2 · 7 min readDebugging Hallucinations in RAG Systems: A Practical Playbook"Just improve the prompt" is a band-aid, not a diagnosis Every RAG hallucination thread on the internet eventually arrives at the same advice: tighten the prompt, tell the model to only use the providhimanitayal.hashnode.dev
SSaksham RanaJun 19 · 5 min readWhy LLMs Hallucinate — The Actual Mechanical ReasonEveryone's heard the word. Fewer people know what's actually happening inside the model when it confidently tells you something completely wrong. It's not a bug. It's not a glitch. It's the model doin2heyytsunami.hashnode.dev
OOmnithiumJun 1 · 13 min readAgent Hallucination Detection and Mitigation in ProductionThe hallucination problem moves from chat to agents When a customer support chatbot invents a refund policy, the damage is usually contained: a confused user, an escalation, a corrected response. But omnithium.hashnode.dev
VVamsi KrishnaMay 27 · 3 min readDay 07: Why confident AI answers still need evidenceThe dangerous hallucinations are not the strange ones. Those get caught. The dangerous ones are fluent, confident, and almost right, a real policy with one wrong number, a real process with one inventblog.vamsiannamreddy.com
SSapotaCorpMay 24 · 8 min readFaithfulness gate: the agent layer most teams skipA B2B SaaS team got an angry email from a customer last quarter. The customer's account team had asked the company's AI assistant whether their plan included SSO. The assistant said yes. The customer'sapotacorpvn.hashnode.dev
